Our goal in this paper is to fill the gap between RGB-based and event-based monocular human pose estimation. In particular, we propose an end-to-end pipeline to predict the skeleton of a subject from the stream of a single event-camera. Figure REF  provides an overview of our methodology. An event-camera collects an asynchronous stream of events of a subject moving in the scene. Instead of tracking events as previous works [1]}, we aggregate them into tensor-like frames. Next, we predict three heatmaps planes of the cuboid surrounding the subject and finally build his final 3D pose through triangulation.
